Using lexical chains for keyword extraction
dc.citation.epage | 1714 | en_US |
dc.citation.issueNumber | 6 | en_US |
dc.citation.spage | 1705 | en_US |
dc.citation.volumeNumber | 43 | en_US |
dc.contributor.author | Ercan, G. | en_US |
dc.contributor.author | Cicekli, I. | en_US |
dc.date.accessioned | 2016-02-08T10:12:28Z | |
dc.date.available | 2016-02-08T10:12:28Z | |
dc.date.issued | 2007-11 | en_US |
dc.department | Department of Computer Engineering | en_US |
dc.description.abstract | Keywords can be considered as condensed versions of documents and short forms of their summaries. In this paper, the problem of automatic extraction of keywords from documents is treated as a supervised learning task. A lexical chain holds a set of semantically related words of a text and it can be said that a lexical chain represents the semantic content of a portion of the text. Although lexical chains have been extensively used in text summarization, their usage for keyword extraction problem has not been fully investigated. In this paper, a keyword extraction technique that uses lexical chains is described, and encouraging results are obtained. © 2007 Elsevier Ltd. All rights reserved. | en_US |
dc.identifier.doi | 10.1016/j.ipm.2007.01.015 | en_US |
dc.identifier.issn | 0306-4573 | en_US |
dc.identifier.uri | http://hdl.handle.net/11693/23343 | en_US |
dc.language.iso | English | en_US |
dc.publisher | Elsevier Ltd | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1016/j.ipm.2007.01.015 | en_US |
dc.source.title | Information Processing and Management | en_US |
dc.subject | Keyword extraction | en_US |
dc.subject | Lexical chains | en_US |
dc.subject | Machine learning | en_US |
dc.subject | Natural language processing | en_US |
dc.subject | Classification (of information) | en_US |
dc.subject | Learning systems | en_US |
dc.subject | Natural language processing systems | en_US |
dc.subject | Semantics | en_US |
dc.subject | Text processing | en_US |
dc.title | Using lexical chains for keyword extraction | en_US |
dc.type | Article | en_US |
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